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Pose Estimation
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Pose Estimation is a computer vision task where the goal is to detect the position and orientation of a person or an object. Usually, this is done by predicting the location of specific keypoints like hands, head, elbows, etc. in case of Human Pose Estimation.
A common benchmark for this task is MPII Human Pose
<span style="color:grey; opacity: 0.6">( Image credit: Real-time 2D Multi-Person Pose Estimation on CPU: Lightweight OpenPose )</span>
논문
이 태스크와 하위 분야의 관련 논문입니다. 실제 성능 비교는 평가 결과에서 확인하세요.
RAG-6DPose: Retrieval-Augmented 6D Pose Estimation via Leveraging CAD as Knowledge Base
DreamJourney: Perpetual View Generation with Video Diffusion Models
Monocular One-Shot Metric-Depth Alignment for RGB-Based Robot Grasping
RGBTrack: Fast, Robust Depth-Free 6D Pose Estimation and Tracking
Beyond Audio and Pose: A General-Purpose Framework for Video Synchronization
STAR-Pose: Efficient Low-Resolution Video Human Pose Estimation via Spatial-Temporal Adaptive Super-Resolution
Reproducible Evaluation of Camera Auto-Exposure Methods in the Field: Platform, Benchmark and Lessons Learned
RA-NeRF: Robust Neural Radiance Field Reconstruction with Accurate Camera Pose Estimation under Complex Trajectories
Human Motion Capture from Loose and Sparse Inertial Sensors with Garment-aware Diffusion Models
PRISM-Loc: a Lightweight Long-range LiDAR Localization in Urban Environments with Topological Maps
Compressed Video Super-Resolution based on Hierarchical Encoding
PoseGRAF: Geometric-Reinforced Adaptive Fusion for Monocular 3D Human Pose Estimation
DETRPose: Real-time end-to-end transformer model for multi-person pose estimation
JENGA: Object selection and pose estimation for robotic grasping from a stack
PF-LHM: 3D Animatable Avatar Reconstruction from Pose-free Articulated Human Images
A large-scale, physically-based synthetic dataset for satellite pose estimation
FCA2: Frame Compression-Aware Autoencoder for Modular and Fast Compressed Video Super-Resolution
ViTaSCOPE: Visuo-tactile Implicit Representation for In-hand Pose and Extrinsic Contact Estimation
ICME 2025 Grand Challenge on Video Super-Resolution for Video Conferencing
EmbodiedGen: Towards a Generative 3D World Engine for Embodied Intelligence
Occlusion-Aware 3D Hand-Object Pose Estimation with Masked AutoEncoders
CHIP: A multi-sensor dataset for 6D pose estimation of chairs in industrial settings
Accurate and efficient zero-shot 6D pose estimation with frozen foundation models
EquiCaps: Predictor-Free Pose-Aware Pre-Trained Capsule Networks
Fluoroscopic Shape and Pose Tracking of Catheters with Custom Radiopaque Markers
LiftVSR: Lifting Image Diffusion to Video Super-Resolution via Hybrid Temporal Modeling with Only 4$\times$RTX 4090s
ArrowPose: Segmentation, Detection, and 5 DoF Pose Estimation Network for Colorless Point Clouds
Princeton365: A Diverse Dataset with Accurate Camera Pose
Monocular 3D Hand Pose Estimation with Implicit Camera Alignment
Hierarchical Scoring with 3D Gaussian Splatting for Instance Image-Goal Navigation
UA-Pose: Uncertainty-Aware 6D Object Pose Estimation and Online Object Completion with Partial References
From Generation to Generalization: Emergent Few-Shot Learning in Video Diffusion Models
A Systematic Investigation on Deep Learning-Based Omnidirectional Image and Video Super-Resolution
Deep Inertial Pose: A deep learning approach for human pose estimation
You Only Estimate Once: Unified, One-stage, Real-Time Category-level Articulated Object 6D Pose Estimation for Robotic Grasping
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.